33 citations
- Ben-Gurion University of the NegevIL1 paper
- California Southern UniversityUS1 paper
- City University of Hong KongHK1 paper
- IkerbasqueES1 paper
- Linköping UniversitySE1 paper
- Universidad de DeustoES1 paper
- University of Applied Sciences St PöltenAT1 paper
- University of Southern CaliforniaUS1 paper
- University of SurreyGB1 paper
- University of UtahUS1 paper
6 papers
Towards Reliable Objective Evaluation Metrics for Generative Singing Voice Separation Models
Paul A. Bereuter, Benjamin Stahl, Mark D. Plumbley +1
Traditional Blind Source Separation Evaluation (BSS-Eval) metrics were originally designed to evaluate linear audio source separation models based on methods such as time-frequency…
Open Your Ears and Take a Look: A State-of-the-Art Report on the Integration of Sonification and Visualization
Kajetan Enge, Elias Elmquist, Valentina Caiola +7
The research communities studying visualization and sonification for data display and analysis share exceptionally similar goals, essentially making data of any kind interpretable…
Theory and investigation of acoustic multiple-input multiple-output systems based on spherical arrays in a room
Hai Morgenstern, Boaz Rafaely, Franz Zotter
Spatial attributes of room acoustics have been widely studied using microphone and loudspeaker arrays. However, systems that combine both arrays, referred to as multiple-input mult…
Auralization based on multi-perspective ambisonic room impulse responses
Kaspar Müller, Franz Zotter
Most often, virtual acoustic rendering employs real-time updated room acoustic simulations to accomplish auralization for a variable listener perspective. As an alternative, we pro…
Perceptual evaluation of listener envelopment using spatial granular synthesis
Stefan Riedel, Matthias Frank, Franz Zotter
Listener envelopment refers to the sensation of being surrounded by sound, either by multiple direct sound events or by a diffuse reverberant sound field. More recently, a specific…
Accuracy Improvement for Fully Convolutional Networks via Selective Augmentation with Applications to Electrocardiogram Data
Lucas Cassiel Jacaruso
Deep learning methods have shown suitability for time series classification in the health and medical domain, with promising results for electrocardiogram data classification. Succ…